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NEURAL_NETWORKS: 作品数：979被引量：1758H指数：16; 导出分析报告; 相关作者：李爱群费树岷宋爱国王一清温秀兰更多>>; 相关机构：东南大学南京航空航天大学北京理工大学中国石油大学（北京）更多>>; 相关期刊：更多>>; 相关基金：国家自然科学基金国家重点基础研究发展计划国家高技术研究发展计划中国博士后科学基金更多>>

Predicting outcomes using neural networks in the intensive care unit: 《World Journal of Clinical Cases》2025年第11期1-11,共11页Gumpeny R Sridhar Venkat Yarabati Lakshmi Gumpeny; Patients in intensive care units(ICUs)require rapid critical decision making.Modern ICUs are data rich,where information streams from diverse sources.Machine learning(ML)and neural networks(NN)can leverage the rich da...; 关键词：Large language models HALLUCINATIONS Supervised learning Unsupervised learning Convoluted neural networks BLACK-BOX WORKFLOW

Data-based neural controls for an unknown continuous-time multi-input system with integral reinforcement: 《Control Theory and Technology》2025年第1期118-130,共13页Yongfeng Lv Jun Zhao Wan Zhang Huimin Chang; Integral reinforcement learning(IRL)is an effective tool for solving optimal control problems of nonlinear systems,and it has been widely utilized in optimal controller design for solving discrete-time nonlinearity.Ho...; 关键词：Adaptive dynamic programming Integral reinforcement Neural networks Heuristic dynamic programming Multi-input system

An optimization-based equilibrium measure describing fixed points of non-equilibrium dynamics:application to the edge of chaos: 《Communications in Theoretical Physics》2025年第3期140-156,共17页Junbin Qiu Haiping Huang; supported by the National Natural Science Foundation of China under Grant No.12122515(HH);Guangdong Provincial Key Laboratory of Magnetoelectric Physics and Devices(Grant No.2022B1212010008);Guangdong Basic and Applied Basic Research Foundation(Grant No.2023B1515040023)。; Understanding neural dynamics is a central topic in machine learning,non-linear physics,and neuroscience.However,the dynamics are non-linear,stochastic and particularly non-gradient,i.e.,the driving force cannot be wr...; 关键词：high-dimensional chaos phase transitions neural networks order parameters statistical physics

FractalNet-LSTM Model for Time Series Forecasting: 《Computers, Materials & Continua》2025年第3期4469-4484,共16页Nataliya Shakhovska Volodymyr Shymanskyi Maksym Prymachenko; Time series forecasting is important in the fields of finance,energy,and meteorology,but traditional methods often fail to cope with the complex nonlinear and nonstationary processes of real data.In this paper,we prop...; 关键词：Time series fractal neural networks forecasting LSTM FractalNet

A paper mill detection model based on citation manipulation paradigm: 《Journal of Data and Information Science》2025年第1期167-187,共21页Jun Zhang Jianhua Liu Haihong E Tianyi Hu Xiaodong Qiao ZiChen Tang; supported by the National Science Foundation of China(Grant No.62176026);Project of“Image Inspection Basic Data and Platform Construction”,Department of Science and Technology Supervision and Integrity Building,Ministry of Science and Technology(Grant No.GXCZ-D-21070106);ISTIC-Taylor&Francis Group Academic Frontier Watch Joint Laboratory Open Grant.; Purpose:In this paper,we develop a heterogeneous graph network using citation relations between papers and their basic information centered around the“Paper mills”papers under withdrawal observation,and we train gra...; 关键词：Paper mills Research integrity Graph neural networks Deep learning

Unsupervised multiplex graph diffusion networks with multi-level canonical correlation analysis for multiplex graph representation learning: 《Science China(Information Sciences)》2025年第3期62-75,共14页Sichao FU Qinmu PENG Yange HE Baokun DU Bin ZOU Xiao-Yuan JING Xinge YOU; supported in part by National Key Research and Development Program of China(Grant No.2022YFF0712300);National Natural Science Foundation of China(Grant No.62172177);Knowledge Innovation Program of Wuhan-Shuguang;Fundamental Research Funds for the Central Universities(HUST)(Grant No.2022JYCXJJ034);Open Research Fund from Shandong Provincial Key Laboratory of Computer Network(Grant No.SKLCN-2021-02)。; In recent years,unsupervised multiplex graph representation learning(UMGRL)has received increasing research interest,which aims to learn discriminative node features from the multiplex graphs supervised by data withou...; 关键词：unsupervised multiplex graph representation learning graph neural networks node classification node clustering

Efficient Estimation of Single-index Models with Deep ReQU Neural Networks: 《Acta Mathematica Sinica,English Series》2025年第2期640-676,共37页Zhihuang Yang Siming Zheng Niansheng Tang; Supported by the National Natural Science Foundation of China (Grant No. 12271472)。; Single-index model offers the greater flexibility of modelling than generalized linear models and also retains the interpretability of the model to some extent. Although many standard approaches such as kernels or pen...; 关键词：Asymptotical normality deep neural networks non-asymptotic estimation error bound semiparametric efficiency single-index models

Exploring the Chameleon Effect of Contextual Dynamics in Temporal Knowledge Graph for Event Prediction: 《Tsinghua Science and Technology》2025年第1期433-455,共23页Xin Liu Yi He Wenxin Tai Xovee Xu Fan Zhou Guangchun Luo; supported by the National Natural Science Foundation of China(Nos.62176043 and 62072077);the Grant SCITLAB-30002 of Intelligent Terminal Key Laboratory of Sichuan Province.; The ability to forecast future events brings great benefits for society and cyberspace in many public safety domains,such as civil unrest,pandemics and crimes.The occurrences of new events are often correlated or depe...; 关键词：temporal knowledge graph event forecasting graph neural networks self-supervised learning explainability

All-optical nonlinear activation functions realized on phasechange photonic integrated circuits with microheaters被引量：1: 《Journal of Semiconductors》2025年第2期122-131,共10页Jiyuan Jiang Bingxin Ding Shiyu Li Xin Zhang Haihua Wang Jie Wu Xiaoyan Liu Zhou Wang Xiaojuan Lian Wen Huang Lei Wang; supported by the National Natural Science Foundation of China(Grant Nos.62104114,62404111);Natural Science Foundation of Jiangsu Province(Grant Nos.BK20240635,BZ2021031);Opening Project of Advanced Integrated Circuit Package and Testing Research Center of Jiangsu Province(Grant No.NTIKFJJ202303);Natural Science Foundation of the Jiangsu Higher Education Institutions of China(Grant No.24KJB510025);Natural Science Research Start-up Foundation of Recruiting Talents of Nanjing University of Posts and Telecommunications(Grant Nos.NY223157,NY223156);Natural Science Foundation of Nanjing University of Posts and Telecommunications(Grant No.NY224140);Project funded by China Postdoctoral Science Foundation(Grant No.2023M732916).; Photonic neural networks have garnered significant attention in recent years due to their ultra-high computational speed,broad bandwidth,and parallel processing capabilities.However,compared to conventional electronic...; 关键词：ONAF Sb_(2)Se_(3) MICROHEATER photonic neural networks

TMC-GCN: Encrypted Traffic Mapping Classification Method Based on Graph Convolutional Networks: 《Computers, Materials & Continua》2025年第2期3179-3201,共23页Baoquan Liu Xi Chen Qingjun Yuan Degang Li Chunxiang Gu; supported by the National Key Research and Development Program of China No.2023YFA1009500.; With the emphasis on user privacy and communication security, encrypted traffic has increased dramatically, which brings great challenges to traffic classification. The classification method of encrypted traffic based...; 关键词：Encrypted traffic classification deep learning graph neural networks multi-layer perceptron graph convolutional networks

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